In general, fingerprints constituted with a great number of ridgelines with streaked pattern have two significant features of being permanent and unique. Therefore, fingerprints are used for criminal investigations from old times.
Particularly, fingerprint matching using a latent fingerprint left in a criminal scene is an effective means for investigation, and many police organizations recently employ a fingerprint matching system using a computer.
For fingerprint matching, as introduced in 3 Minutiae-Based Methods in Handbook of Fingerprint Recognition (Springer 2003) (Non-Patent Document 1), conventionally, feature-point matching using endpoints and bifurcations (combination of the both is called as fingerprint feature point or Minutia), for example, is used broadly.
For example, between high-quality fingerprint images such as inked fingerprints, a sufficient number of minutiae can be extracted from the both fingerprint images. Therefore, high matching accuracy can be guaranteed.
However, in a case where one of those is a latent fingerprint of small region, a minutia extractable range is narrow. Thus, a sufficient number of minutiae cannot be extracted. As a result, it is not possible to perform matching with high accuracy.
Various methods have been proposed for overcoming such issue.
For example, there is a method which not only uses the minutiae but also uses pores, incipient ridges, scars, and the like as new feature amounts.
Further, “Pores and Ridges: Fingerprint Matching Using level 3 Features” (Non-Patent Document 2) proposes use of the pores.
Further, many image matchings using ridgeline shapes are disclosed and, as a related technique thereof, there is known a system (image feature extraction device) which extracts rough feature shapes of fingerprint ridgelines by performing dimensional compression processing (KL Transform) on fingerprint images and extracts a fingerprint image that fits the feature shape from a database as a matching-target image (Patent Document 1).
In fingerprint matching, fingerprint cores (referred to as “cores” hereinafter) are optimum as the information used for specifying matching regions and position alignment. In manual examination executed by an expert examiner, it is widely performed to align the positions according to the cores and compare the ridgeline shapes in the vicinity thereof by visual inspection.
Also proposed is a core extraction method using skeleton images of fingerprint images. In automatic extraction processing, skeleton images in which ridgelines are transformed into skeletons are normally used.
With this method, the skeleton forming an innermost recurve is specified from a skeleton mage, and the vertex is detected and determined as a core, for example.
Note here that the innermost recurve is the skeleton that is located at the innermost side. In a sense, the innermost recurve can also be considered as a loop-like (hoof-like) skeleton.
Criminal identification terms such as the core and the innermost recurve (or innermost loop) and the like are defined in “The Science of Fingerprints-Classification and Uses” (Non-Patent Document 3).
However, core extraction accuracy is an issue when automating the processing.
As disclosed in 3.6 Singularity and Core Detection of Handbook of Fingerprint Recognition (Springer 2003), for example, the mainstream of the core extraction methods proposed heretofore is a method using the ridgeline direction (orientation or vector).
While there is an advantage with this method that it is not susceptible to local noises and the core can be extracted stably, there is such a shortcoming that detailed position detection cannot be expected.    Patent Document 1: Japanese Unexamined Patent Publication Hei 10-177650    Non-Patent Document 1: Handbook of Fingerprint Recognition (Springer 2003)    Non-Patent Document 2: “Pores and Ridges: Fingerprint Matching Using Level3 Features”    Non-Patent Document 3: “The Science of Fingerprints-Classification and Uses”
Feature vectors and the like required for matching cannot be extracted stably from low-quality latent fingerprints with Patent Document 1 described above, so that there is a limit in contributing to improving matching accuracy. Further, there is also such shortcoming that the calculation amount and time for executing matching through pattern matching become tremendous when executing fingerprint matching processing.
Furthermore, there is such shortcoming with the related techniques of Non-Patent Documents 1 and 2 that detailed fingerprint core positions cannot be extracted. Further, with the method using skeleton images for fingerprint matching, cores cannot be detected accurately in a case where a noise is included in the skeleton images or the vicinity of the vertex is a complicated shape.
An object of the present invention is to improve the shortcomings of the related techniques and to provide a fingerprint core extraction device for fingerprint matching capable of extracting fingerprint cores used for matching of fingerprint images with high accuracy, a fingerprint matching system, a fingerprint core extraction method, and a program therefore.